1. Field of the Invention
This invention relates to methodology for utilizing data mining techniques in the area of distribution centers management.
2. Introduction to the Invention
Data mining techniques are known and include disparate technologies, like neural networks, which can work to an end of efficiently discovering valuable, non-obvious information from a large collection of data. The data, in turn, may arise in fields ranging from e.g., marketing, finance, manufacturing, or retail.
We have now discovered novel methodology for exploiting the advantages inherent generally in data mining technologies, in the particular field of distribution centers management applications.
Our work proceeds in the following way.
We have recognized that a typical and important xe2x80x9cthree-partxe2x80x9d paradigm for presently effecting distribution centers management, is a largely subjective, human paradigm, and therefore exposed to all the vagaries and deficiencies otherwise attendant on human procedures. In particular, the three-part paradigm we have in mind works in the following way.
First, a distribution center manager develops a demand database comprising a compendium of individual demand historyxe2x80x94e.g., the demand""s response to historical distribution situations. Secondly, and independently, the distribution center manager develops in his mind a distribution database comprising the distribution center manager""s personal, partial, and subjective knowledge of objective retail facts culled from e.g., the marketing literature, the business literature, or input from colleagues or salespersons. Thirdly, the distribution center manager subjectively correlates in his mind the necessarily incomplete and partial distribution database, with the demand database, in order to promulgate a prescribed individual""s demand distribution centers management evaluation and cure.
This three-part paradigm is part science and part art, and captures one aspect of the problems associated with distribution centers management. However, as suggested above, it is manifestly a subjective paradigm, and therefore open to human vagaries.
We now disclose a novel computer method which can preserve the advantages inherent in this three-part paradigm, while minimizing its incompleteness and attendant subjectivities that otherwise inure in a technique heretofore entirely reserved for human realization.
To this end, in a first aspect of the present invention, we disclose a novel computer method comprising the steps of:
i) providing a demand database comprising a compendium of demand history;
ii) providing a distribution database comprising a compendium of at least one of distribution centers management solutions, distribution centers information, and distribution centers diagnostics; and
iii) employing a data mining technique for interrogating said demand and distribution databases for generating an output data stream, said output data stream correlating a demand problem with a distribution solution.
The novel method preferably comprises a further step of updating the step i) demand database, so that it can cumulatively track the demand history as it develops over time. For example, this step i) of updating the demand database may include the results of employing the step iii) data mining technique. Also, the method may comprise a step of refining an employed data mining technique in cognizance of pattern changes embedded in each database as a consequence of distribution results and updating the demand database.
The novel method preferably comprises a further step of updating the step ii) distribution database, so that it can cumulatively track an ever increasing and developing technical distribution centers management literature. For example, this step ii) of updating the distribution database may include the effects of employing a data mining technique on the demand database. Also, the method may comprise a step of refining an employed data mining technique in cognizance of pattern changes embedded in each database as a consequence of distribution results and updating the distribution database.
The novel method may employ advantageously a wide array of step iii) data mining techniques for interrogating the demand and distribution databases for generating an output data stream, which output data stream correlates a demand problem with a distribution solution. For example, the data mining technique may comprise inter alia employment of the following functions for producing output data: classification-neural, classification-tree, clustering-geographic, clustering-neural, factor analysis, or principal component analysis, or expert systems.
In a second aspect of the present invention, we disclose a program storage device readable by machine to perform method steps for providing an distribution centers management database, the method comprising the steps of:
i) providing a demand database comprising a compendium of individual demand history;
ii) providing a distribution database comprising a compendium of at least one of distribution centers management solutions, distribution centers information, and distribution centers diagnostics; and
iii) employing a data mining technique for interrogating said demand and distribution databases for generating an output data stream, said output data stream correlating a demand problem with a distribution solution.
In a third aspect of the present invention, we disclose a computer comprising:
i) means for inputting a demand database comprising a compendium of individual demand history;
ii) means for inputting a distribution database comprising a compendium of at least one of distribution centers management solutions, distribution centers information, and distribution centers diagnostics;
iii) means for employing a data mining technique for interrogating said distribution databases;
iv) means for generating an output data stream, said output data stream correlating a demand problem with a distribution solution.
We have now summarized the invention in several of its aspects or manifestations. It may be observed, in sharp contrast with the prior art discussed above comprising the three part subjective paradigm approach to the problem of distribution centers management, that the summarized invention utilizes inter alia, the technique of data mining. We now point out, firstly, that the technique of data mining is of such complexity and utility, that as a technique, in and of itself, it cannot be used in any way as an available candidate solution for enhancing distribution centers management, to the extent that the problem of distribution centers management is only approached within the realm of the human-subjective solution to distribution centers management. Moreover, to the extent that the present invention uses computer techniques including e.g., data mining techniques, to an end of solving a problem of distribution centers management, it is not in general obvious within the nominal context of the problem as we have defined it and the technique of data mining, how they are in fact to be brought into relationship in order to provide a pragmatic solution to the problem of distribution centers management. It is, rather, an aspect of the novelty and unobviousness of the present invention that it discloses, on the one hand, the possibility for using the technique of data mining within the context of distribution centers management, and, moreover, on the other hand, discloses illustrative methodology that is required to in fact pragmatically bring the technique of data mining to bear on the actuality of solving the problem of distribution centers management.